1. Segmentation of Touching Characters in Devnagari & Bangla Scripts Using Fuzzy MultiFactorial Analysis Presented By: Sanjeev Maharjan St. Xavier’s College

2. Contents  Background  Introducing Devnagari & Bangla Scripts  Segmentation in Devnagari & Bangla  Touching Characters in OCR  Fuzzy Mutifactorial Analysis (Solving Touching Character Problem)  Result  Conclusion

3. BACKGROUND  Document Analysis System  OCR for Document Analysis  How OCR works?

4. BACKGROUND (Document Analysis System)  Facilitates transfer of information on a paper document to the computer systems without intensive manual keying

5. BACKGROUND (OCR for Document Analysis System)  Recognizes the well-shaped and well-spaced characters from the scanned paper document  Converts those recognized characters to machine- editable format

6. BACKGROUND (How OCR Works???)  Take Text Image as Input  Segmentation of Text Segment the text into lines Segment the lines into words Segment the words into characters  Character Recognition Extract distinct features of character Map the character with predefined character set

7. INTRODUCING ‘Devnagari’ & ‘Bangla’ SCRIPTS  Writing style Left to right  50 basic characters in both scripts  Vowels take modified shape (allograph)  Consonants combine to form compound characters  More than 250 characters  Characters of the word are combined by ‘headline’ or ‘Shirorekha’ or ‘Dikka’

8. INTRODUCING ‘Devnagari’ & ‘Bangla’ SCRIPTS FIGURE: Three parts in Devnagari Script (a) & Bangla Script (b)

9. SEGMENTATION IN ‘Devnagari’ & ‘Bangla’ SCRIPTS  Headline is detected in text by row wise sum of black pixels  Position between two consecutive headlines where projection profile height is least, segments into lines  Vertical projection pixel profile segments words  Removing the headline segments words into individual characters

10. SEGMENTATION IN ‘Devnagari’ & ‘Bangla’ SCRIPTS

11. TOUCHING CHARACTERS IN OCR  Efficiency of OCR relies on segmentation error rate  Segmentation is based on connectivity analysis  Invalid Touching Characters degrade segmentation efficiency  Touching characters are more frequent in the Devnagari & Bangla Scripts

12. TOUCHING CHARACTERS IN OCR (Research Observation)  Mostly constitutes of two characters  Not valid characters  Have larger aspect ratio than isolated character  Vertical thickness of the black bob at touching position is small  At most of the touching positions single black run is encountered  Touch mostly at middle of the middle zone  Uncommon stroke patterns are generated at touching points

13. FUZZY MULTIFACTORIAL ANALYSIS  Wang defined the concept of factor spaces(1982)  He defined ‘factor’ as primary time with possible states & characteristics  Eg: If factor is length, then 1mtr, 10 mtr etc are its states and long, short are its characteristics

14. FUZZY MULTIFACTORIAL ANALYSIS  H.X. Li & V.C. Yen discussed 4 factors: Measurable Factors: (like time) Nominal Factors: (like religion) Degree/Fuzzy Factors (Degree of Similarity) Switch/Boolean Factors (0/1)  Multiple fuzzy factors are analyzed to identify & segment the touching characters

15. FUZZY MULTIFACTORIAL ANALYSIS (Identifying Touching Characters)  Factors Considered: Dissimilarity factor (F md ) Aspect Ratio (F ar )  F md =1-d off /d d off =minimum similarity distance for a target character against a set of stored prototypes d=the offset distance used by character classifiers  F ar= e a /1+e a a=w/h, w, h=width and height of minimum upright bounding box of character  Multifactorial Function (Mid)=1/2(F md + F ar )

16. FUZZY MULTIFACTORIAL ANALYSIS (Finding Cut Positions)  Factors Considered F ic (Inverse crossing count)= c-1 c = vertical crossing count for a pixel column. F mt (measure of blob thickness)=1-t/T t = no. of black pixel found in one column scan T = height of the characters middle zone F dm (degree of Middleness) F dm =min(l1,l2)/max(l1,l2)

17. FUZZY MULTIFACTORIAL ANALYSIS (Finding Cut Positions)  Factors Considered: F up (Up Stroke pattern) F low (Lower Stroke Pattern)

18. FUZZY MULTIFACTORIAL ANALYSIS (Finding Cut Positions)  For ‘m’ pixel columns, all five factors are evaluated, forming nx5 evaluation matrix  Multifactorial function

19. FUZZY MULTIFACTORIAL ANALYSIS (Confirming Cut Column) 1.List optimal cut positions identified 2.Take cut position with highest multifactor evaluation value 3.Segment the touching character resulting two characters say p1 & p2 4.Send p1 and p2 to character classifier 5.If p1 & p2 both are recognized then cut position confirmed else if p1 is recognized then take cut position with 2 nd highest multifactor evaluation repeat from step 3 to segment p2 else if p2 is recognized then take cut position with 2 nd highest multifactor evaluation repeat from step 3 to segment p1 else take cut position with 2 nd highest multifactor evaluation repeat from step 3

20. FUZZY MULTIFACTORIAL ANALYSIS (Confirming Cut Column) Touching Character After identification of cut positions Separation using Right-Most Cut Position Character Classifier identifies as ‘Ka’ Character Classifier identifies as ‘La’ Character Classifier identifies as ‘Ma’ Separating Again

21. RESULTS (By using Fuzzy Multifactorial Analysis)  Still problem in identifying the touching characters  Segmentation accuracy is 98.92% and 98.47% in Devnagari and Bangla Scripts repectively  System Throughput (T) is calculated as : T= C/t where C is total number of characters properly recognized by the OCR, and t is total time elapsed for the operation  System Efficiency (E) is calculated as E=(Nv*100)/Nt where Nv is the number of valid cut columns and Nt is total number of cut columns checked to find the valid cuts.

22. CONCLUSION  Touching characters being one of the major problem for Nepali OCR at the present  Use of Fuzzy Multifactorial Analysis would certainly contribute in minimising the joining errors in Nepali OCR

23. Resource Material  Paper on “Segmentation of Touching Characters Printed Devnagari and Bangla Scripts Using Fuzzy Multifactorial Analysis” By: and Utpal GarainBidyut B. Chaudhari